Performance Comparison of Face Recognition using Transform Domain Techniques

The biometrics is a powerful tool to authenticate a person for multiple applications. The face recognition is better biometrics compared to other biometric traits as the image can be captured without the knowledge and cooperation of a person. In this paper, we propose Performance Comparison of Face Recognition using Transform Domain Techniques (PCFTD). The face databases L – Spacek, JAFFE and NIR are considered. The features of face are generated using wavelet families such as Haar, Symelt and DB1 by considering approximation band only. The face features are also generated using magnitudes of FFTs. The test image features are compared with database features using Euclidian Distance (ED). The performance parameters such as FAR, FRR, TSR and EER computed using wavelet families and FFT. It is observed that the performance of FFT is better compared to wavelet families. The success rate of recognition is 100% for L – Spacek and JAFFE face databases as compared to 95% for NIR face databases.